13 results
Search Results
Now showing 1 - 10 of 13
- ItemClimate change and potential distribution of potato (Solanum tuberosum) crop cultivation in Pakistan using Maxent(Springfield, MO : AIMS Press, 2021) Khalil, Tayyaba; Asad, Saeed A.; Khubaib, Nusaiba; Baig, Ayesha; Atif, Salman; Umar, Muhammad; Kropp, Jürgen P.; Pradhan, Prajal; Baig, SofiaThe impacts of climate change are projected to become more intense and frequent. One of the indirect impacts of climate change is food insecurity. Agriculture in Pakistan, measured fourth best in the world, is already experiencing visible adverse impacts of climate change. Among many other food sources, potato crop remains one of the food security crops for developing nations. Potatoes are widely cultivated in Pakistan. To assess the impact of climate change on potato crop in Pakistan, it is imperative to analyze its distribution under future climate change scenarios using Species Distribution Models (SDMs). Maximum Entropy Model is used in this study to predict the spatial distribution of Potato in 2070 using two CMIP5 models for two climate change scenarios (RCP 4.5 and RCP 8.5). 19 Bioclimatic variables are incorporated along with other contributing variables like soil type, elevation and irrigation. The results indicate slight decrease in the suitable area for potato growth in RCP 4.5 and drastic decrease in suitable area in RCP 8.5 for both models. The performance evaluation of the model is based on AUC. AUC value of 0.85 suggests the fitness of the model and thus, it is applicable to predict the suitable climate for potato production in Pakistan. Sustainable potato cultivation is needed to increase productivity in developing countries while promoting better resource management and optimization.
- ItemNear Real-Time Biophysical Rice (Oryza sativa L.) Yield Estimation to Support Crop Insurance Implementation in India(Basel : MDPI, 2020) Arumugam, Ponraj; Chemura, Abel; Schauberger, Bernhard; Gornott, ChristophImmediate yield loss information is required to trigger crop insurance payouts, which are important to secure agricultural income stability for millions of smallholder farmers. Techniques for monitoring crop growth in real-time and at 5 km spatial resolution may also aid in designing price interventions or storage strategies for domestic production. In India, the current government-backed PMFBY (Pradhan Mantri Fasal Bima Yojana) insurance scheme is seeking such technologies to enable cost-efficient insurance premiums for Indian farmers. In this study, we used the Decision Support System for Agrotechnology Transfer (DSSAT) to estimate yield and yield anomalies at 5 km spatial resolution for Kharif rice (Oryza sativa L.) over India between 2001 and 2017. We calibrated the model using publicly available data: namely, gridded weather data, nutrient applications, sowing dates, crop mask, irrigation information, and genetic coefficients of staple varieties. The model performance over the model calibration years (2001–2015) was exceptionally good, with 13 of 15 years achieving more than 0.7 correlation coefficient (r), and more than half of the years with above 0.75 correlation with observed yields. Around 52% (67%) of the districts obtained a relative Root Mean Square Error (rRMSE) of less than 20% (25%) after calibration in the major rice-growing districts (>25% area under cultivation). An out-of-sample validation of the calibrated model in Kharif seasons 2016 and 2017 resulted in differences between state-wise observed and simulated yield anomalies from –16% to 20%. Overall, the good ability of the model in the simulations of rice yield indicates that the model is applicable in selected states of India, and its outputs are useful as a yield loss assessment index for the crop insurance scheme PMFBY.
- ItemIncorporating Biodiversity into Biogeochemistry Models to Improve Prediction of Ecosystem Services in Temperate Grasslands: Review and Roadmap(Basel : MDPI, 2020) Van Oijen, Marcel; Barcza, Zoltán; Confalonieri, Roberto; Korhonen, Panu; Kröel-Dulay, György; Lellei-Kovács, Eszter; Louarn, Gaëtan; Louault, Frédérique; Martin, Raphaël; Moulin, Thibault; Movedi, Ermes; Picon-Cochard, Catherine; Rolinski, Susanne; Viovy, Nicolas; Wirth, Stephen Björn; Bellocchi, GianniMulti-species grasslands are reservoirs of biodiversity and provide multiple ecosystem services, including fodder production and carbon sequestration. The provision of these services depends on the control exerted on the biogeochemistry and plant diversity of the system by the interplay of biotic and abiotic factors, e.g., grazing or mowing intensity. Biogeochemical models incorporate a mechanistic view of the functioning of grasslands and provide a sound basis for studying the underlying processes. However, in these models, the simulation of biogeochemical cycles is generally not coupled to simulation of plant species dynamics, which leads to considerable uncertainty about the quality of predictions. Ecological models, on the other hand, do account for biodiversity with approaches adopted from plant demography, but without linking the dynamics of plant species to the biogeochemical processes occurring at the community level, and this hampers the models’ capacity to assess resilience against abiotic stresses such as drought and nutrient limitation. While setting out the state-of-the-art developments of biogeochemical and ecological modelling, we explore and highlight the role of plant diversity in the regulation of the ecosystem processes underlying the ecosystems services provided by multi-species grasslands. An extensive literature and model survey was carried out with an emphasis on technically advanced models reconciling biogeochemistry and biodiversity, which are readily applicable to managed grasslands in temperate latitudes. We propose a roadmap of promising developments in modelling.
- ItemSimultaneous Calibration of Grapevine Phenology and Yield with a Soil–Plant–Atmosphere System Model Using the Frequentist Method(Basel : MDPI, 2021-8-20) Yang, Chenyao; Menz, Christoph; Fraga, Helder; Reis, Samuel; Machado, Nelson; Malheiro, Aureliano C.; Santos, João A.Reliable estimations of parameter values and associated uncertainties are crucial for crop model applications in agro-environmental research. However, estimating many parameters simultaneously for different types of response variables is difficult. This becomes more complicated for grapevines with different phenotypes between varieties and training systems. Our study aims to evaluate how a standard least square approach can be used to calibrate a complex grapevine model for simulating both the phenology (flowering and harvest date) and yield of four different variety–training systems in the Douro Demarcated Region, northern Portugal. An objective function is defined to search for the best-fit parameters that result in the minimum value of the unweighted sum of the normalized Root Mean Squared Error (nRMSE) of the studied variables. Parameter uncertainties are estimated as how a given parameter value can determine the total prediction variability caused by variations in the other parameter combinations. The results indicate that the best-estimated parameters show a satisfactory predictive performance, with a mean bias of −2 to 4 days for phenology and −232 to 159 kg/ha for yield. The corresponding variance in the observed data was generally well reproduced, except for one occasion. These parameters are a good trade-off to achieve results close to the best possible fit of each response variable. No parameter combinations can achieve minimum errors simultaneously for phenology and yield, where the best fit to one variable can lead to a poor fit to another. The proposed parameter uncertainty analysis is particularly useful to select the best-fit parameter values when several choices with equal performance occur. A global sensitivity analysis is applied where the fruit-setting parameters are identified as key determinants for yield simulations. Overall, the approach (including uncertainty analysis) is relatively simple and straightforward without specific pre-conditions (e.g., model continuity), which can be easily applied for other models and crops. However, a challenge has been identified, which is associated with the appropriate assumption of the model errors, where a combination of various calibration approaches might be essential to have a more robust parameter estimation.
- ItemPerformance of seasonal forecasts for the flowering and veraison of two major Portuguese grapevine varieties(Amsterdam [u.a.] : Elsevier, 2023) Yang, Chenyao; Ceglar, Andrej; Menz, Christoph; Martins, Joana; Fraga, Helder; Santos, João A.Seasonal phenology forecasts are becoming increasingly demanded by winegrowers and viticulturists. Forecast performance needs to be investigated over space and time before practical applications. We assess seasonal forecast performance (skill, probability and accuracy) in predicting flowering and veraison stages of two representative varieties in Portugal over 1993–2017. The state-of-the-art forecast system ECMWF-SEAS5 provides 7-month seasonal forecasts and is coupled with a locally adapted phenology model. Overall, findings illustrate the dependence of forecast performance on initialization timings, regions and predicting subjects (stages and varieties). Forecast performance improves by delaying the initialization timing and only forecasts initialized on April 1st show better skills than climatology on predicting phenology terciles (early/normal/late). The considerable bias of daily values of seasonal climate predictions can represent the main barrier to accurate forecasts. Better prediction performance is consistently found in Central-Southern regions compared to Northern regions, attributing to an earlier phenology occurrence with a shorter forecast length. Comparable predictive skills between flowering and veraison for both varieties imply better predictability in summer. Consequently, promising seasonal phenology predictions are foreseen in Central-Southern wine regions using forecasts initialized on April 1st with approximately 1–2/3–4 months lead time for flowering/veraison: potential prediction errors are ∼2 weeks, along with an overall moderate forecast skill on categorical events. However, considerable inter-annual variability of forecast performance over the same classified phenology years reflects the substantial influence of climate variability. This may represent the main challenge for reliable forecasts in Mediterranean regions. Recommendations are suggested for methodological innovations and practical applications towards reliable regional phenology forecasts.
- ItemClimate change impacts on European arable crop yields: Sensitivity to assumptions about rotations and residue management(Amsterdam [u.a.] : Elsevier, 2022) Faye, Babacar; Webber, Heidi; Gaiser, Thomas; Müller, Christoph; Zhang, Yinan; Stella, Tommaso; Latka, Catharina; Reckling, Moritz; Heckelei, Thomas; Helming, Katharina; Ewert, FrankMost large scale studies assessing climate change impacts on crops are performed with simulations of single crops and with annual re-initialization of the initial soil conditions. This is in contrast to the reality that crops are grown in rotations, often with sizable proportion of the preceding crop residue to be left in the fields and varying soil initial conditions from year to year. In this study, the sensitivity of climate change impacts on crop yield and soil organic carbon to assumptions about annual model re-initialization, specification of crop rotations and the amount of residue retained in fields was assessed for seven main crops across Europe. Simulations were conducted for a scenario period 2040–2065 relative to a baseline from 1980 to 2005 using the SIMPLACE1 framework. Results indicated across Europe positive climate change impacts on yield for C3 crops and negative impacts for maize. The consideration of simulating rotations did not have a benefit on yield variability but on relative yield change in response to climate change which slightly increased for C3 crops and decreased for C4 crops when rotation was considered. Soil organic carbon decreased under climate change in both simulations assuming a continuous monocrop and plausible rotations by between 1% and 2% depending on the residue management strategy.
- ItemEvaluating the grassland NPP dynamics in response to climate change in Tanzania(Amsterdam [u.a.] : Elsevier Science, 2021) Zarei, Azin; Chemura, Abel; Gleixner, Stephanie; Hoff, HolgerLivestock is important for livelihoods of millions of people across the world and yet climate change risk and impacts assessments are predominantly on cropping systems. Climate change has significant impacts on Net Primary Production (NPP) which is a grassland dynamics indicator. This study aimed to analyze the spatio-temporal changes of NPP under climate scenario RCP2.6 and RCP8.5 in the grassland of Tanzania by 2050 and link this to potential for key livestock species. To this end, a regression model to estimate NPP was developed based on temperature (T), precipitation (P) and evapotranspiration (ET) during the period 2001–2019. NPP fluctuation maps under future scenarios were produced as difference maps of the current (2009–2019) and future (2050). The vulnerable areas whose NPP is mostly likely to get affected by climate change in 2050 were identified. The number of livestock units in grasslands was estimated according to NPP in grasslands of Tanzania at the Provincial levels. The results indicate the mean temperature and evapotranspiration are projected to increase under both emission scenarios while precipitation will decrease. NPP is significantly positively correlated with Tmax and ET and projected increases in these variables will be beneficial to NPP under climate change. Increases of 17% in 2050 under RCP8.5 scenario are projected, with the southern parts of the country projected to have the largest increase in NPP. The southwest areas showed a decreasing trend in mean NPP of 27.95% (RCP2.6) and 13.43% (RCP8.5). The highest decrease would occur in the RCP2.6 scenario in Ruvuma Province, by contrast, the mean NPP value in the western, eastern, and central parts would increase in 2050 under both Scenarios, the largest increase would observe in Kilimanjaro, Dar-Es-Salaam and Dodoma Provinces. It was found that the number of grazing livestock such as cattle, sheep, and goats will increase in the Tanzania grasslands under both climate scenarios. As the grassland ecosystems under intensive exploitation are fragile ecosystems, a combination of improving grassland productivity and grassland conservation under environmental pressures such as climate change should be considered for sustainable grassland management.
- ItemAnalysis of Olive Grove Destruction by Xylella fastidiosa Bacterium on the Land Surface Temperature in Salento Detected Using Satellite Images(Basel : MDPI, 2021-9-16) Semeraro, Teodoro; Buccolieri, Riccardo; Vergine, Marzia; De Bellis, Luigi; Luvisi, Andrea; Emmanuel, Rohinton; Marwan, NorbertAgricultural activity replaces natural vegetation with cultivated land and it is a major cause of local and global climate change. Highly specialized agricultural production leads to extensive monoculture farming with a low biodiversity that may cause low landscape resilience. This is the case on the Salento peninsula, in the Apulia Region of Italy, where the Xylella fastidiosa bacterium has caused the mass destruction of olive trees, many of them in monumental groves. The historical land cover that characterized the landscape is currently in a transition phase and can strongly affect climate conditions. This study aims to analyze how the destruction of olive groves by X. fastidiosa affects local climate change. Land surface temperature (LST) data detected by Landsat 8 and MODIS satellites are used as a proxies for microclimate mitigation ecosystem services linked to the evolution of the land cover. Moreover, recurrence quantification analysis was applied to the study of LST evolution. The results showed that olive groves are the least capable forest type for mitigating LST, but they are more capable than farmland, above all in the summer when the air temperature is the highest. The differences in the average LST from 2014 to 2020 between olive groves and farmland ranges from 2.8 °C to 0.8 °C. Furthermore, the recurrence analysis showed that X. fastidiosa was rapidly changing the LST of the olive groves into values to those of farmland, with a difference in LST reduced to less than a third from the time when the bacterium was identified in Apulia six years ago. The change generated by X. fastidiosa started in 2009 and showed more or less constant behavior after 2010 without substantial variation; therefore, this can serve as the index of a static situation, which can indicate non-recovery or non-transformation of the dying olive groves. Failure to restore the initial environmental conditions can be connected with the slow progress of the uprooting and replacing infected plants, probably due to attempts to save the historic aspect of the landscape by looking for solutions that avoid uprooting the diseased plants. This suggests that social-ecological systems have to be more responsive to phytosanitary epidemics and adapt to ecological processes, which cannot always be easily controlled, to produce more resilient landscapes and avoid unwanted transformations.
- ItemAgriculture's Historic Twin-Challenge Toward Sustainable Water Use and Food Supply for All(Lausanne : Frontiers Media, 2020) Jägermeyr, JonasA sustainable and just future, envisioned by the UN's 2030 Agenda for Sustainable Development, puts agricultural systems under a heavy strain. The century-old quandary to provide ever-growing human populations with sufficient food takes on a new dimension with the recognition of environmental limits for agricultural resource use. To highlight challenges and opportunities toward sustainable food security in the twenty first century, this perspective paper provides a historical account of the escalating pressures on agriculture and freshwater resources alike, supported by new quantitative estimates of the ascent of excessive human water use. As the transformation of global farming into sustainable forms is unattainable without a revolution in agricultural water use, water saving and food production potentials are put into perspective with targets outlined by the Sustainable Development Goals (SDGs). The literature body and here-confirmed global estimates of untapped opportunities in farm water management indicate that these measures could sustainably intensify today's farming systems at scale. While rigorous implementation of sustainable water withdrawals (SDG 6.4) might impinge upon 5% of global food production, scaling-up water interventions in rainfed and irrigated systems could over-compensate such losses and further increase global production by 30% compared to the current situation (SDG 2.3). Without relying on future technological fixes, traditional on-farm water and soil management provides key strategies associated with important synergies that needs better integration into agro-ecological landscape approaches. Integrated strategies for sustainable intensification of agriculture within planetary boundaries are a potential way to attain several SDGs, but they are not yet receiving attention from high-level development policies. © Copyright © 2020 Jägermeyr.
- ItemSustainable food protein supply reconciling human and ecosystem health: A Leibniz Position(Amsterdam [u.a.] : Elsevier, 2020) Weindl, Isabelle; Ost, Mario; Wiedmer, Petra; Schreiner, Monika; Neugart, Susanne; Klopsch, Rebecca; Kühnhold, Holger; Kloas, Werner; Henkel, Ina M.; Schlüter, Oliver; Bußler, Sara; Bellingrath-Kimura, Sonoko D.; Ma, Hua; Grune, Tilman; Rolinski, Susanne; Klaus, SusanneMany global health risks are related to what and how much we eat. At the same time, the production of food, especially from animal origin, contributes to environmental change at a scale that threatens boundaries of a safe operating space for humanity. Here we outline viable solutions how to reconcile healthy protein consumption and sustainable protein production which requires a solid, interdisciplinary evidence base. We review the role of proteins for human and ecosystem health, including physiological effects of dietary proteins, production potentials from agricultural and aquaculture systems, environmental impacts of protein production, and mitigation potentials of transforming current production systems. Various protein sources from plant and animal origin, including insects and fish, are discussed in the light of their health and environmental implications. Integration of available knowledge is essential to move from a dual problem description (“healthy diets versus environment”) towards approaches that frame the food challenge of reconciling human and ecosystem health in the context of planetary health. This endeavor requires a shifting focus from metrics at the level of macronutrients to whole diets and a better understanding of the full cascade of health effects caused by dietary proteins, including health risks from food-related environmental degradation. © 2020